ArticleClinical and translational gastroenterology2020
Oncogenic Features in Histologically Normal Mucosa: Novel Insights Into Field Effect From a Mega-Analysis of Colorectal Transcriptomes.
Article in Clinical and translational gastroenterology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 17 citations in OpenAlex.
- Association of germline variants with KRAS-mutation status in colorectal cancer.Scientific reports · 2026Article
- Association of TIGIT and CD155 with KRAS, NRAS, BRAF, PIK3CA, and AKT Gene Mutations, MSI Status, and Cytokine Profiles in Colorectal Cancer.International journal of molecular sciences · 2026Article
- TIM-3/Galectin-9 Immune Axis in Colorectal Cancer in Relation to KRAS, NRAS, BRAF, PIK3CA, AKT1 Mutations, MSI Status, and the Cytokine Milieu.International journal of molecular sciences · 2025Article
- Exploring the Chemopreventive Effect of Medication on Gene Expression Linked to Colorectal Cancer: An Observational and Mendelian Randomization Analysis in Healthy Colon Mucosa.International journal of molecular sciences · 2024Observational
- Associations of SEMA7A, SEMA4D, ADAMTS10, and ADAM8 with KRAS, NRAS, BRAF, PIK3CA, and AKT Gene Mutations, Microsatellite Instability Status, and Cytokine Expression in Colorectal Cancer Tissue.Current issues in molecular biology · 2024Article
- B7H3 Role in Reshaping Immunosuppressive Landscape in MSI and MSS Colorectal Cancer Tumours.Cancers · 2023Article
- Do Elevated YKL-40 Levels Drive the Immunosuppressive Tumor Microenvironment in Colorectal Cancer? Assessment of the Association of the Expression of YKL-40, MMP-8, IL17A, and PD-L1 with Coexisting Type 2 Diabetes, Obesity, and Active Smoking.Current issues in molecular biology · 2023Article
- Overexpression and Role of HHLA2, a Novel Immune Checkpoint, in Colorectal Cancer.International journal of molecular sciences · 2023Article
- Article
- C9orf16 represents the aberrant genetic programs and drives the progression of PDAC.BMC cancer · 2022Article
- Transcriptomic Response to Calcium in Normal Colon Organoids is Impacted by Colon Location and Sex.Cancer prevention research (Philadelphia, Pa.) · 2022Article
- Significance of Hypermethylation of Tumor-Suppressor Genes PTGER4 and ZNF43 at CpG Sites in the Prognosis of Colorectal Cancer.International journal of molecular sciences · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
introductionColorectal cancer is a common malignancy that can be cured when detected early, but recurrence among survivors is a persistent risk. A field effect of cancer in the colon has been reported and could have implications for surveillance, but studies to date have been limited. A joint analysis of pooled transcriptomic data from all available bulk RNA-sequencing data sets of healthy, histologically normal tumor-adjacent, and tumor tissues was performed to provide an unbiased assessment of field effect.
methodsA novel bulk RNA-sequencing data set from biopsies of nondiseased colon from screening colonoscopy along with published data sets from the Genomic Data Commons and Sequence Read Archive were considered for inclusion. Analyses were limited to samples with a quantified read depth of at least 10 million reads. Transcript abundance was estimated with Salmon, and downstream analysis was performed in R.
resultsA total of 1,139 samples were analyzed in 3 cohorts. The primary cohort consisted of 834 independent samples from 8 independent data sets, including 462 healthy, 61 tumor-adjacent, and 311 tumor samples. Tumor-adjacent gene expression was found to represent an intermediate state between healthy and tumor expression. Among differentially expressed genes in tumor-adjacent samples, 1,143 were expressed in patterns similar to tumor samples, and these genes were enriched for cancer-associated pathways. DISCUSSION: Novel insights into the field effect in colorectal cancer were generated in this mega-analysis of the colorectal transcriptome. Oncogenic features that might help explain metachronous lesions in cancer survivors and could be used for surveillance and risk stratification were identified.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.